---
language:
- en
license: apache-2.0
library_name: diffusers
pipeline_tag: text-to-video
tags:
- text-to-video
- video-generation
- generative-ai
- diffusion
- pytorch
- transformers
- diffusers
---

# 🎬 Text-to-Video Generation Model

A text-to-video generation project that converts natural language
prompts into short AI-generated videos using a diffusion-based
text-to-video model.

## 📌 Overview

This project demonstrates text-to-video generation using a
pretrained diffusion model from the Hugging Face ecosystem.

The system takes a textual description as input and generates
a sequence of video frames, which are combined into an MP4 video.

### Pipeline

Text Prompt
     ↓
Text Encoder
     ↓
Diffusion Model
     ↓
Video Frames
     ↓
MP4 Video

---

## ✨ Features

- Text-to-video generation
- Natural language prompts
- Diffusion-based video generation
- GPU acceleration with CUDA
- MP4 video export
- Compatible with Hugging Face Diffusers
- Can be executed using Google Colab

---

## 🤖 Model Information

### Base Model

`damo-vilab/text-to-video-ms-1.7b`

### Model Architecture

Diffusion-based text-to-video generation model.

### Framework

- PyTorch
- Hugging Face Diffusers
- Hugging Face Transformers
- Accelerate

---

## 🚀 Usage

Install the required libraries:

```bash
pip install diffusers transformers accelerate torch imageio imageio-ffmpeg